Proceedings of the 5th International Conference on Applied Sciences, Mathematics, and Informatics (ICASMI 2024)

<Previous Article In Volume
Next Article In Volume>

Perceptual Linear Prediction Feature Extraction For Lampung Voice to Text Transcription (Case Study: Lampung Pepadun Dialect A)

Authors
Mohamad Zainudin1, Akmal Junaidi1, *, Favorisen R. Lumbanraja1, Aristoteles1, Tristiyanto1
1Faculty of Mathematics and Natural Science, Department of Computer Science, University of Lampung, Bandar Lampung, Indonesia
*Corresponding author. Email: akmal.junaidi@fmipa.unila.ac.id
Corresponding Author
Akmal Junaidi
Available Online 27 May 2025.
DOI
10.2991/978-94-6463-730-4_10How to use a DOI?
Keywords
Perceptual Linear Prediction (PLP); Speech-to-Text (STT); Lampung Language; Language Preservation; Feature Extraction
Abstract

Lampung language is one of the endangered regional languages in Indonesia, with the number of native speakers continuing to decline. One of the efforts to preserve this language is to utilize Speech-to-Text (STT) technology, which enables voice-to-text transcription to efficiently document the language. This research uses the Perceptual Linear Prediction (PLP) method for feature extraction from the voice signals of native speakers of Lampung Pepadun Dialect A. Perceptual Linear Prediction (PLP) was chosen for its ability to mimic human auditory perception, so that it can produce acoustic features suitable for the speech recognition process. The extraction process was performed on voice data from four speakers who uttered sentences in Lampung. The extraction results show that the PLP method is effective in capturing variations in acoustic characteristics, such as intensity, mid-frequency, and pronunciation stability. Each Perceptual Linear Prediction (PLP) coefficient provides significant information about the relevant sound elements for recognition. With these results, the developed Speech-to-Text (STT) system has the potential to be used in Lampung language preservation efforts through digital documentation and automatic transcription.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 5th International Conference on Applied Sciences, Mathematics, and Informatics (ICASMI 2024)
Series
Advances in Physics Research
Publication Date
27 May 2025
ISBN
978-94-6463-730-4
ISSN
2352-541X
DOI
10.2991/978-94-6463-730-4_10How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Mohamad Zainudin
AU  - Akmal Junaidi
AU  - Favorisen R. Lumbanraja
AU  - Aristoteles
AU  - Tristiyanto
PY  - 2025
DA  - 2025/05/27
TI  - Perceptual Linear Prediction Feature Extraction For Lampung Voice to Text Transcription (Case Study: Lampung Pepadun Dialect A)
BT  - Proceedings of the 5th International Conference on Applied Sciences, Mathematics, and Informatics (ICASMI 2024)
PB  - Atlantis Press
SP  - 108
EP  - 117
SN  - 2352-541X
UR  - https://doi.org/10.2991/978-94-6463-730-4_10
DO  - 10.2991/978-94-6463-730-4_10
ID  - Zainudin2025
ER  -